Grandparents Raising Grandchildren in Canada: A Profile of Skipped Generation Families
Bibliographic record
Abstract
Only recently has the topic of Canadian grandparents raising grandchildren begun to receive attention from the media, politicians and researchers. Between 1991 and 2001 there was a 20% increase in the number of Canadian children under 18 who were living with grandparents with no parent present in the home. Using custom tabulation data from the 1996 Canadian Census, this paper presents a profile of grandparents raising grandchildren in skipped generation households (households which only include grandparents and grandchildren) and their household characteristics. There were almost 27,000 Canadian grandparents raising grandchildren in skipped generation families in 1996. These grandparents were disproportionately female (59%), of First Nations Heritage (17%) and out of the labour force (57%). One in three households of grandparent caregivers included a grandparent with a disability and a similar proportion had a household income less than $15,000 per annum. Marked differences were apparent when grandmothers and grandfathers in skipped generation households were compared. Grandmother caregivers were poorer, less likely to be married, more likely to be out of the labour force and more than twice as likely to provide 60 or more hours per week of unpaid childcare than were grandfathers. Implications for further research, policy and practice are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".